A number of social software systems give their users reputation/trust scores, which can be voted on by other users. This, however, is not without problems: when carelessly designed, the ability of users to vote down other users' reputations
can lead to extortion rackets:
It didn't take long for a group calling itself the Sims Mafia to figure out how to use this mechanic to shake down new users when they arrived in the game. The dialog would go something like this:
"Hi! I see from your hub that you're new to the area. Give me all your Simoleans or my friends and I will make it impossible to rent a house.”
"What are you talking about?"
"I'm a member of the Sims Mafia, and we will all mark you as untrustworthy, turning your hub solid red (with no more room for green), and no one will play with you. You have five minutes to comply. If you think I'm kidding, look at your hub-three of us have already marked you red. Don't worry, we'll turn it green when you pay…"
The solution to this is to keep positive and negative feedback separate, and have the latter go through moderators (who, presumably, will spot any shenanigans) before making it public.
I'd love to see someone try an approach like Google's PageRank to this problem, where the feedback someone leaves is weighted by their own feedback. Even better would be some sort of hubs-and-authorities algorithm, so people who tend to make good decisions about who to trust over time get weighted more heavily.
You could also have seperate 'views' into this system based on a web of trust approach, where I see people I've rated and those I've rated rated as carrying more weight.
In addition as well as the kinds of feedback they tend to leave should matter to. If someone leaves thousands of 0/10 feedbacks then 0/10 feedbacks shouldn't be counted as negatively as a 2/10 feedback from someone who generatelly leaves 9/10 and 10/10 feedbacks.